Cognitive load assessment through EEG: A dataset from arithmetic and Stroop tasksMendeley Data by Ali Nirabi, Faridah Abd Rahman, Mohamed Hadi Habaebi, Khairul Azami Sidek, Siti Yusoff

“…By providing a solid foundation for the development of algorithms capable of detecting and classifying stress levels, the dataset supports innovations in non-invasive monitoring tools and contributes to personalized healthcare solutions that can adapt to the cognitive states of users. …”
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Comparing FIB-4, VCTE, pSWE, 2D-SWE, and MRE Thresholds and Diagnostic Accuracies for Detecting Hepatic Fibrosis in Patients with MASLD: A Systematic Review and Meta-Analysis by Mitchell Patrick Wilson, Ranjit Singh, Shyam Mehta, Mohammad Hassan Murad, Christopher Fung, Gavin Low

“…<b>Conclusions</b>: A FIB-4 threshold of <0.75 and modality-dependent thresholds (VCTE < 7 kPa; pSWE <3 kPa; 2D-SWE <5 kPa; and MRE <2.5 kPa) would achieve sensitivities of around 90% when defining low-risk MASLD in population screening. A modified two-tier algorithm aligning with existing Society of Radiologists in Ultrasound guidelines would improve risk stratification accuracies compared to existing guidelines by European and American liver societies.…”
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An Environment Recognition Algorithm for Staircase Climbing Robots by Yanjie Liu, Yanlong Wei, Chao Wang, Heng Wu

“…Currently, while there are LiDAR-based algorithms that focus either on step geometry detection or scene mapping, few comprehensive algorithms exist that address both step geometry perception and scene mapping for staircases. …”
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A New Approach Based on Metaheuristic Optimization Using Chaotic Functional Connectivity Matrices and Fractal Dimension Analysis for AI-Driven Detection of Orthodontic Growth and D... by Orhan Cicek, Yusuf Bahri Özçelik, Aytaç Altan

“…The proposed model, with its low computational complexity, successfully handles the nonlinear dynamics in C2, C3, and C4 vertebral images, enabling accurate detection of growth and developmental stages. …”
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Prediction of Hypertension Patients with Machine Learning Algorithm by Eko Priyono

“…Worldwide, the prevalence of hypertension reaches approximately 30%, with only 50% of cases being diagnosed and a low level of treatment adherence. Hypertension symptoms are often invisible, making early detection crucial to preventing serious complications. …”
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Research on Spam Filters Based on NB Algorithm by Su Shengyue

“…The SpamAssassin dataset is used in this study to explore the use of the Naive Bayes (NB) algorithm for spam detection. The algorithm demonstrated high accuracy and efficiency in classifying large-scale text data, achieving an accuracy of 97.74%, a recall rate of 96.60%, and a precision rate of 96.8%, with an F1 score of 0.97. …”
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Surface defect detection on bolt surface using a real-time fine-tuned YOLOv6 model by Chhaya Gupta, Nasib Singh Gill, Preeti Gulia, Faeiz M. Alserhani, Piyush Kumar Shukla, J. Shreyas

“…This mitigates semantic loss, reduces information loss, and eliminates the low-resolution feature layer. The backbone design of the proposed YOLOBolt employs the Hybrid Extraction of Features Algorithm (HEFA) for feature extraction. …”
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Trends and Variability of North Pacific Polar Lows by Fei Chen, Hans von Storch

“…The 6-hourly 1948–2010 NCEP 1 reanalyses have been dynamically downscaled for the region of the North Pacific. With a detecting-and-tracking algorithm, the climatology of North Pacific Polar Lows has been constructed. …”
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Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…The practical significance of the proposed trajectory features and the possibility of their implementation in the development of an algorithm for recognizing low-flying low-speed radar targets using passive coherent radar systems was established. …”
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CGDU-DETR: An End-to-End Detection Model for Ship Detection in Day–Night Transition Environments by Wei Wu, Xiyu Fan, Zhuhua Hu, Yaochi Zhao

“…To address the limitations of traditional methods in complex lighting conditions (e.g., strong reflections, low light), we designed a novel CG-Net model based on cascaded group attention and introduced a dynamic feature upsampling algorithm, effectively enhancing the model’s ability to extract multi-scale features and detect targets in complex backgrounds. …”
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Spatial Shape-Aware Network for Elongated Target Detection by Shaowen Xu, Der-Horng Lee

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HIDS-RPL: A Hybrid Deep Learning-Based Intrusion Detection System for RPL in Internet of Medical Things Network by Abdelwahed Berguiga, Ahlem Harchay, Ayman Massaoudi

“…We evaluate the proposed algorithm to detect intrusions using the benchmark CIC-DDoS2019 dataset. …”
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Multisensor Diffusion-Driven Optical Image Translation for Large-Scale Applications by Joao Gabriel Vinholi, Marco Chini, Anis Amziane, Renato Machado, Danilo Silva, Patrick Matgen

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Study on the effect of pulsed eddy current lift-off characteristics for feeding metallic foreign objects detection in coal mine crushers by Benchang Meng, Zezheng Zhuang, Jiahao Ma, Sihai Zhao

“…Abstract This study addresses the challenges of low accuracy and poor timeliness in feeding metallic foreign object detection during high-output continuous crushing operations in coal mines. …”
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Anti-interference algorithm of wireless channel for IoT communication by Ling TAN, Yong ZHUANG

“…In IoT communication,the anti-interference of wireless channel is influenced by various factors.Multi-antenna system has significant effect for promoting anti-interference of channel,whose complexity and performance in signal detection need further improvement.The QR decomposition detection algorithm in signal detection of multi-antenna system has low computational complexity,but the algorithm performance is poor.In order to improve the performance of QR decomposition detection algorithm,a QR decomposition algorithm based on ML criterion and decision candidate mechanism was proposed,and the performance of the algorithm was analyzed.The ML criterion was used to estimate the initial level of the detection,and a reliable decision was adopted in the other detection layer.Candidate points were introduced in unreliable case and the optimal candidate were selected from the feedback.The algorithm could significantly improve the system interference,and propagation error were greatly reduced in the decision feedback.The experimental results show that the proposed algorithm can improve the performance of the IoT system effectively with certain complexity.…”
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Anti-interference algorithm of wireless channel for IoT communication by Ling TAN, Yong ZHUANG

“…In IoT communication,the anti-interference of wireless channel is influenced by various factors.Multi-antenna system has significant effect for promoting anti-interference of channel,whose complexity and performance in signal detection need further improvement.The QR decomposition detection algorithm in signal detection of multi-antenna system has low computational complexity,but the algorithm performance is poor.In order to improve the performance of QR decomposition detection algorithm,a QR decomposition algorithm based on ML criterion and decision candidate mechanism was proposed,and the performance of the algorithm was analyzed.The ML criterion was used to estimate the initial level of the detection,and a reliable decision was adopted in the other detection layer.Candidate points were introduced in unreliable case and the optimal candidate were selected from the feedback.The algorithm could significantly improve the system interference,and propagation error were greatly reduced in the decision feedback.The experimental results show that the proposed algorithm can improve the performance of the IoT system effectively with certain complexity.…”
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Spectrum‐sensing algorithm based on graph feature fusion by Shanshan Wu, Guobing Hu, Bin Gu

“…Thus, compared to existing algorithms, except block range‐ and energy‐detection‐based methods, the proposed algorithm demonstrates the best spectrum‐sensing performance under low SNRs and channel‐fading conditions, while achieving the lowest computational complexity. …”
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Accelerating the k-Means++ Algorithm by Using Geometric Information by Guillem Rodriguez Corominas, Maria J. Blesa, Christian Blum

“…Real-world use cases include social network analysis, medical imaging, market segmentation, and anomaly detection, to name a few. In this paper, we propose an acceleration of the exact k-means++ algorithm using geometric information, specifically the Triangle Inequality and additional norm filters, along with a two-step sampling procedure. …”
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A Low-Complexity Expectation Propagation Detector for OTFS by Xumin Pu, Zhinan Sun, Wanli Wen, Qianbin Chen, Shi Jin

“…The proposed algorithm only requires log-linear complexity. In addition, simulation results show that the proposed algorithm not only has the advantage of low complexity but also has good performance, which achieves a tradeoff between performance and complexity.…”
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An automated approach to identify sarcasm in low-resource language. by Shumaila Khan, Iqbal Qasim, Wahab Khan, Aurangzeb Khan, Javed Ali Khan, Ayman Qahmash, Yazeed Yasin Ghadi

“…Sarcasm detection has emerged due to its applicability in natural language processing (NLP) but lacks substantial exploration in low-resource languages like Urdu, Arabic, Pashto, and Roman-Urdu. …”
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